1 00:00:00,120 --> 00:00:35,560 Speaker 1: Welcome. You are now listening to the Professional profession. Hey, 2 00:00:35,600 --> 00:00:37,879 Speaker 1: Professional home Girls is the kid of a name from 3 00:00:37,880 --> 00:00:40,599 Speaker 1: the PSD podcast, the only place where you would hear 4 00:00:40,840 --> 00:00:43,839 Speaker 1: interviews from black women an honestly on stories that will 5 00:00:43,920 --> 00:00:46,839 Speaker 1: enlighten and expand on taboo topics. Now, if you hear 6 00:00:46,920 --> 00:00:49,920 Speaker 1: someone that sounds familiar, mind the business that pays you child. 7 00:00:50,360 --> 00:00:53,120 Speaker 1: If you like the PhD podcast, please rate, review and 8 00:00:53,159 --> 00:00:57,200 Speaker 1: subscribe on Apple Podcasts. Please five star reviews only hold 9 00:00:57,200 --> 00:01:00,200 Speaker 1: me down, don't hold me up. 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Please keep in mind that 19 00:01:28,240 --> 00:01:30,360 Speaker 1: all of my guests are nonnes so let's again this 20 00:01:30,400 --> 00:01:34,400 Speaker 1: week's episode. So thank you so much to our infectious 21 00:01:34,400 --> 00:01:36,640 Speaker 1: disease dr for coming back to the show to answer 22 00:01:36,720 --> 00:01:41,000 Speaker 1: some more questions on the coronavirus. So, to my guests, 23 00:01:41,160 --> 00:01:47,319 Speaker 1: have you been doing lately? Overall, I've been okay. Obviously, 24 00:01:47,400 --> 00:01:51,400 Speaker 1: it's been very stressful, I believe since the last TRAM 25 00:01:51,600 --> 00:01:56,920 Speaker 1: was going because there was a spike in cases. And 26 00:01:57,200 --> 00:02:00,520 Speaker 1: I'm currently in Rhode Island. So we'll want to very 27 00:02:00,560 --> 00:02:05,240 Speaker 1: few states in which cases continue to either go down 28 00:02:05,520 --> 00:02:10,320 Speaker 1: or remain stable. Unfortunately, a lot of places in the 29 00:02:10,400 --> 00:02:17,639 Speaker 1: country cases or skyrocketing, especially Florida, Texas, Arizona, California. So 30 00:02:18,680 --> 00:02:23,520 Speaker 1: I am very luffy that my state is very blessed 31 00:02:24,280 --> 00:02:29,160 Speaker 1: and I'm overall in a good place. What are your 32 00:02:29,200 --> 00:02:34,920 Speaker 1: thousand the numbers rising back up, Well, it makes me 33 00:02:35,040 --> 00:02:41,120 Speaker 1: really sad, to be honest. Unfortunately, places like Texas and 34 00:02:41,360 --> 00:02:46,800 Speaker 1: Florida that really didn't shut down like it makes me 35 00:02:46,919 --> 00:02:52,240 Speaker 1: sad because a lot of places did shut down, and 36 00:02:52,760 --> 00:02:57,440 Speaker 1: a lot of people lost their jobs or had significant 37 00:02:58,280 --> 00:03:03,160 Speaker 1: decrease in their income um And it's traumatic for a 38 00:03:03,200 --> 00:03:07,000 Speaker 1: lot of people, very very traumatic too, and scary not 39 00:03:07,080 --> 00:03:08,600 Speaker 1: to be able to go to word, not to be 40 00:03:08,639 --> 00:03:12,600 Speaker 1: able to go outside. Now we have all these precautionous 41 00:03:12,639 --> 00:03:16,720 Speaker 1: and so the whole overall hope was that we were 42 00:03:17,080 --> 00:03:21,600 Speaker 1: shut down for a short period of time in order 43 00:03:21,840 --> 00:03:25,520 Speaker 1: too for the greater good, in order to dramatically decrease 44 00:03:26,000 --> 00:03:32,200 Speaker 1: the number of cases. Unfortunately, there were multiple parts of 45 00:03:32,240 --> 00:03:37,480 Speaker 1: the country for political reasons, not based ice scient too 46 00:03:39,120 --> 00:03:42,600 Speaker 1: make conscious decisions not to do this, and now in 47 00:03:42,720 --> 00:03:46,520 Speaker 1: those states there are higher number of cases. I think 48 00:03:46,520 --> 00:03:49,320 Speaker 1: in California. California it's just so big, it was just 49 00:03:49,400 --> 00:03:55,280 Speaker 1: really difficult to control. But definitely Texas, Florida, it really 50 00:03:55,320 --> 00:03:58,240 Speaker 1: didn't shut down. People still were going to Florida for 51 00:03:59,080 --> 00:04:07,839 Speaker 1: spring breaks. Masks weren't mandatory. And now, unfortunately, say I 52 00:04:07,880 --> 00:04:12,720 Speaker 1: had a huge outbreak with COVID nineteen, and I honestly 53 00:04:12,800 --> 00:04:17,039 Speaker 1: do feel bad for people in those states because our 54 00:04:17,120 --> 00:04:21,320 Speaker 1: hope was that we would be like Italy Spain and 55 00:04:21,440 --> 00:04:25,000 Speaker 1: that we have a huge spike and then the case 56 00:04:25,080 --> 00:04:28,120 Speaker 1: was dramatically decrease and we can open things back up. 57 00:04:29,520 --> 00:04:32,000 Speaker 1: Mm hmm. So do you think that we are on 58 00:04:32,040 --> 00:04:33,960 Speaker 1: the brink of the second wave or are we still 59 00:04:33,960 --> 00:04:40,640 Speaker 1: in the first wave? I I honestly think that we are. 60 00:04:40,839 --> 00:04:45,479 Speaker 1: It's just a prolonged Firth wave at this point, because 61 00:04:45,960 --> 00:04:50,120 Speaker 1: you have to ask yourself that the did the states 62 00:04:50,160 --> 00:04:52,920 Speaker 1: that are having higher numbers that they really have things 63 00:04:53,040 --> 00:04:58,920 Speaker 1: under control? A second wave assumes that you had a 64 00:04:59,040 --> 00:05:03,560 Speaker 1: large number of case. This the public health policies and 65 00:05:03,640 --> 00:05:09,000 Speaker 1: governmental policies were put in place where where, which resulted 66 00:05:09,080 --> 00:05:14,600 Speaker 1: in the cases being dramatically decreased or no cases, and 67 00:05:14,680 --> 00:05:17,919 Speaker 1: then you're having a spike. That is not the case 68 00:05:17,960 --> 00:05:21,200 Speaker 1: in a lot of these places. What happened was there 69 00:05:21,279 --> 00:05:26,120 Speaker 1: was maybe a marginal decrease in cases and then now 70 00:05:26,440 --> 00:05:32,200 Speaker 1: it's just flourishing. If you look at certain places like Arizona, 71 00:05:32,279 --> 00:05:35,600 Speaker 1: is just the curve is going up up, And so 72 00:05:35,760 --> 00:05:41,720 Speaker 1: I honestly question whether or not these states that are 73 00:05:41,760 --> 00:05:47,359 Speaker 1: now in cricenses actually had the outbreak under control in 74 00:05:47,400 --> 00:05:52,559 Speaker 1: the first place. What were your thoughts on people saying 75 00:05:52,600 --> 00:05:56,640 Speaker 1: that the numbers was rising due to the protests. So 76 00:05:57,080 --> 00:06:03,559 Speaker 1: I would really challenged that thinking because if you look 77 00:06:03,640 --> 00:06:10,360 Speaker 1: at so I personally participated in protests here where I am. 78 00:06:10,400 --> 00:06:17,000 Speaker 1: If you look at the news footage from CNN, from 79 00:06:17,120 --> 00:06:25,000 Speaker 1: um MSNBC, most people were wearing masks. The majority of 80 00:06:25,000 --> 00:06:30,120 Speaker 1: people were bringing maks. So I, yes, it's a risk, 81 00:06:30,839 --> 00:06:32,760 Speaker 1: Please don't get me wrong. It was a lot of 82 00:06:32,800 --> 00:06:37,080 Speaker 1: people that consiated together, but at least people were wearing 83 00:06:37,160 --> 00:06:43,600 Speaker 1: masks and that dramatically decreased. Uh, excuse me, the risk 84 00:06:43,680 --> 00:06:49,719 Speaker 1: of transmission. However, I it's hard for me to believe 85 00:06:49,800 --> 00:06:54,560 Speaker 1: without hard facts that the protests were the trigger. What 86 00:06:54,800 --> 00:06:59,640 Speaker 1: I really think happened where people in communities where masks 87 00:06:59,680 --> 00:07:05,520 Speaker 1: were not a requirement, there were very There wasn't really 88 00:07:05,760 --> 00:07:09,960 Speaker 1: a lot of regulations for people, you know, remaining distance, 89 00:07:11,400 --> 00:07:14,920 Speaker 1: for limiting the number of people in one area. I 90 00:07:14,960 --> 00:07:21,600 Speaker 1: think those things were unfortunately issue. So let me actually 91 00:07:21,640 --> 00:07:24,440 Speaker 1: bring you back and trying to put some fashion regards 92 00:07:24,440 --> 00:07:28,680 Speaker 1: to the math. So we've heard of like many protests 93 00:07:28,680 --> 00:07:33,440 Speaker 1: all over the country. Okay, however, you know Trump recently 94 00:07:33,600 --> 00:07:42,360 Speaker 1: had of rally campaign rally in Arizona. If I'm not mistaken, 95 00:07:43,320 --> 00:07:48,400 Speaker 1: there's an outbreak of people who went to that rally 96 00:07:48,560 --> 00:07:52,800 Speaker 1: and the Secret Service and everything you know, associated with 97 00:07:52,880 --> 00:07:57,720 Speaker 1: that rally. People were seeing more COVID cases And if 98 00:07:57,760 --> 00:08:01,520 Speaker 1: you look at the footage, most of those people didn't 99 00:08:01,520 --> 00:08:06,400 Speaker 1: have masks. And so then now you see a clear 100 00:08:06,520 --> 00:08:11,680 Speaker 1: example of a large group of people gathering, you know, 101 00:08:11,800 --> 00:08:15,600 Speaker 1: without mask and see what can happen. So there may 102 00:08:15,640 --> 00:08:19,360 Speaker 1: have been you know, outbreak associated with the protest. I 103 00:08:19,400 --> 00:08:21,280 Speaker 1: don't know. I don't know the fact that I haven't 104 00:08:21,520 --> 00:08:25,160 Speaker 1: heard anything on the news, that doesn't mean that it 105 00:08:25,240 --> 00:08:29,440 Speaker 1: didn't happen. But you know, we do know that there 106 00:08:29,480 --> 00:08:34,560 Speaker 1: have been the outbreak associated with recent Trump rallies, and 107 00:08:34,720 --> 00:08:41,720 Speaker 1: these people specifically work and wearing masks. So that's an example. 108 00:08:41,840 --> 00:08:47,680 Speaker 1: Like I understand, people have their political affiliation, they feel 109 00:08:47,720 --> 00:08:51,840 Speaker 1: strongly about whatever issue, and they feel that they need 110 00:08:51,880 --> 00:08:56,400 Speaker 1: to either go for a rally or protest. I understand that, however, 111 00:08:56,440 --> 00:08:59,920 Speaker 1: if we could just wear a mask that's gonna death 112 00:09:00,000 --> 00:09:03,320 Speaker 1: in itly protect you and if you were to be sick, 113 00:09:03,400 --> 00:09:09,360 Speaker 1: protect others from you. Do you think that people are 114 00:09:09,640 --> 00:09:14,920 Speaker 1: not still not taking this serious. Yeah, people definitely aren't 115 00:09:14,960 --> 00:09:22,360 Speaker 1: taking it seriously. People. Oh people. I still think that 116 00:09:22,600 --> 00:09:27,680 Speaker 1: this is a conspiracy and that people like people that 117 00:09:27,880 --> 00:09:32,079 Speaker 1: the media is making up these numbers, and that it's 118 00:09:32,120 --> 00:09:35,880 Speaker 1: really not as bad as people are saying it is. 119 00:09:36,920 --> 00:09:40,200 Speaker 1: But it's really difficult because I've seen so many people 120 00:09:40,280 --> 00:09:43,760 Speaker 1: die from this disease. I've seen it hit the elderly, 121 00:09:43,920 --> 00:09:47,480 Speaker 1: I've seen it hit the most vulnerable people, people who 122 00:09:47,640 --> 00:09:52,959 Speaker 1: are non verbal, you know, developmentally delay who really rely 123 00:09:53,120 --> 00:09:56,000 Speaker 1: on caregivers to care for them. I've seen them die, 124 00:09:56,320 --> 00:10:00,480 Speaker 1: I've seen them get six. I've seen young people, healthy, 125 00:10:00,679 --> 00:10:05,320 Speaker 1: young people get sick from this infection. So it's not 126 00:10:05,480 --> 00:10:08,719 Speaker 1: something that's made up. It's a deadly disease that I 127 00:10:08,760 --> 00:10:11,960 Speaker 1: would not wish on my worst enemy. And it really 128 00:10:12,080 --> 00:10:18,559 Speaker 1: is insulting to hear somebody say that, oh, people are 129 00:10:18,600 --> 00:10:23,480 Speaker 1: just making it up, and because that's not true, and 130 00:10:23,800 --> 00:10:28,760 Speaker 1: I think a lot of people have this mindset, how 131 00:10:28,800 --> 00:10:34,120 Speaker 1: do I say this? I think, so COVID is only 132 00:10:34,160 --> 00:10:39,160 Speaker 1: affected over three million people in this country, we have 133 00:10:39,480 --> 00:10:43,840 Speaker 1: many more people in this country, so you still have 134 00:10:44,040 --> 00:10:47,800 Speaker 1: subset of populations who have never seen a COVID case, 135 00:10:48,520 --> 00:10:51,520 Speaker 1: like they don't if they've never been sick. They have 136 00:10:51,720 --> 00:10:56,160 Speaker 1: family and friends and haven't been sick. Just doing the numbers, 137 00:10:56,240 --> 00:11:00,000 Speaker 1: so I can truly understand how people in that situation 138 00:11:00,000 --> 00:11:03,880 Speaker 1: ation can believe that this is a hoax, this is 139 00:11:03,960 --> 00:11:07,240 Speaker 1: something that's made up. But as a health care professional, 140 00:11:07,440 --> 00:11:14,040 Speaker 1: especially as an infectious disease doctor, it is real and 141 00:11:14,160 --> 00:11:19,800 Speaker 1: people are dying, and this is not something that you 142 00:11:19,960 --> 00:11:24,959 Speaker 1: want to get Everyone who said, oh, I don't believe 143 00:11:25,000 --> 00:11:27,000 Speaker 1: in it, I don't think you need to wear a 144 00:11:27,040 --> 00:11:31,200 Speaker 1: mask and actually gets COVID. They all regret saying that, 145 00:11:31,240 --> 00:11:33,480 Speaker 1: Oh I didn't believe in it. Oh you know I 146 00:11:33,559 --> 00:11:35,480 Speaker 1: was out here and not wearing a mask. They all 147 00:11:35,520 --> 00:11:39,520 Speaker 1: regret it because it's that terrible. But I but I'm 148 00:11:39,559 --> 00:11:42,520 Speaker 1: hoping that we could get to a point where people 149 00:11:42,559 --> 00:11:47,199 Speaker 1: actually believe what we're saying and that they don't have 150 00:11:47,280 --> 00:11:52,240 Speaker 1: to learn from experience. Yeah, I want my mask everywhere. 151 00:11:52,559 --> 00:11:55,559 Speaker 1: I don't play no games. No, I think you should. 152 00:11:55,640 --> 00:11:59,800 Speaker 1: And it's look, I've been wearing a mask since month, 153 00:12:00,920 --> 00:12:04,520 Speaker 1: every day, all day. It is very inconvenient. I don't 154 00:12:04,600 --> 00:12:09,000 Speaker 1: like it. However, you know, I don't want to be sick, 155 00:12:10,120 --> 00:12:14,320 Speaker 1: you know, I really it really is for the greater good. 156 00:12:14,679 --> 00:12:19,600 Speaker 1: And I think it's important for people to think beyond themselves. 157 00:12:20,679 --> 00:12:24,760 Speaker 1: I feel that I have a very easy to think about. 158 00:12:26,320 --> 00:12:30,760 Speaker 1: I have a feema me mentality. Oh it's not affecting me, Oh, 159 00:12:30,920 --> 00:12:33,840 Speaker 1: this is a wearing a mask is inconvenient for me. 160 00:12:34,520 --> 00:12:39,960 Speaker 1: It's infringing with my personal rights. I don't want to 161 00:12:40,200 --> 00:12:44,280 Speaker 1: social distance because I'm missing out on my wedding, on 162 00:12:44,440 --> 00:12:49,719 Speaker 1: my relatives wedding, or my birthday. I understand that this 163 00:12:49,840 --> 00:12:55,360 Speaker 1: is inconvenient for everybody, but were making sure your distance, 164 00:12:56,520 --> 00:12:59,600 Speaker 1: making sure wearing a mask is going to help. The 165 00:12:59,679 --> 00:13:04,520 Speaker 1: gray are good even if you've never been sick. And 166 00:13:04,600 --> 00:13:08,200 Speaker 1: if people can think, how can I what can I 167 00:13:08,240 --> 00:13:13,960 Speaker 1: do to help the greater good? To help somebody bought somebody? 168 00:13:14,000 --> 00:13:17,280 Speaker 1: Is that I don't even know. If we were all 169 00:13:17,320 --> 00:13:22,120 Speaker 1: as Americans in this frame of mind, I think that 170 00:13:22,200 --> 00:13:24,840 Speaker 1: we would be in a better place. But it's not 171 00:13:25,000 --> 00:13:28,760 Speaker 1: too late. If we are to hunker down and really 172 00:13:29,440 --> 00:13:34,120 Speaker 1: start thinking about others and not just our needs, our wants, 173 00:13:34,120 --> 00:13:38,280 Speaker 1: our desires, and really take this thing seriously, I think 174 00:13:38,440 --> 00:13:43,920 Speaker 1: that we can turn this thing around. It's just really 175 00:13:44,000 --> 00:13:49,360 Speaker 1: difficult from a financial standpoint because just look at people 176 00:13:49,679 --> 00:13:54,320 Speaker 1: or states or counties who actually shut down now and 177 00:13:54,800 --> 00:13:59,480 Speaker 1: people lost shops, people out for unemployment. Now you're asking 178 00:13:59,520 --> 00:14:04,120 Speaker 1: them this shut shut down again after they've been allowed 179 00:14:04,160 --> 00:14:07,320 Speaker 1: to go back to work, been allowed to do other things. 180 00:14:07,400 --> 00:14:12,680 Speaker 1: So it's just really unfortunate situation. I really truly do 181 00:14:13,040 --> 00:14:16,840 Speaker 1: feel bad for those places that are being hit heavy, 182 00:14:16,880 --> 00:14:22,880 Speaker 1: because it really it's a not only like, it's a 183 00:14:22,960 --> 00:14:26,920 Speaker 1: heavy emotional and physical toll, especially for people who are 184 00:14:26,920 --> 00:14:31,720 Speaker 1: on the front line. The the e m t s, 185 00:14:31,840 --> 00:14:40,440 Speaker 1: police officers, nurses positions advance um like nurse practitioners position 186 00:14:40,480 --> 00:14:46,360 Speaker 1: assist Like. It's really a heavy, heavy, heavy toll, and 187 00:14:46,440 --> 00:14:50,840 Speaker 1: now you're expecting people to really work crazy hours and 188 00:14:51,040 --> 00:14:54,280 Speaker 1: really do this emotional toll since March in a lot 189 00:14:54,320 --> 00:14:59,920 Speaker 1: of places, it's really difficult. Can you apply with the call? 190 00:15:00,120 --> 00:15:08,400 Speaker 1: The test is yes, So atibody test in general, well, 191 00:15:08,480 --> 00:15:10,600 Speaker 1: let's just back up, just want to make sure we're 192 00:15:10,600 --> 00:15:16,440 Speaker 1: all on the same page. When you become sick with 193 00:15:16,720 --> 00:15:21,800 Speaker 1: a virus, let's say, or let's say the flu, well, 194 00:15:21,840 --> 00:15:24,040 Speaker 1: well let's not do this flue. Let's say you get 195 00:15:24,080 --> 00:15:31,360 Speaker 1: sick with covid okay, which is a coronavirus. Your body, 196 00:15:33,360 --> 00:15:37,200 Speaker 1: your body amuses to ramp us to fight the infection. 197 00:15:38,240 --> 00:15:43,120 Speaker 1: When you recover, your body will remember that you were 198 00:15:43,200 --> 00:15:48,040 Speaker 1: expected with that virus. And how it does that is 199 00:15:48,080 --> 00:15:53,720 Speaker 1: that it creates antibodies. So the reason why antibodies are 200 00:15:53,800 --> 00:15:59,080 Speaker 1: important is because if you were to get reinfected with 201 00:15:59,160 --> 00:16:04,600 Speaker 1: that virus, your immune system already has the tools to 202 00:16:04,640 --> 00:16:08,880 Speaker 1: fite that infection and you will be less sick than 203 00:16:08,920 --> 00:16:12,840 Speaker 1: you were the first time. So what the antibody test 204 00:16:12,960 --> 00:16:18,160 Speaker 1: is doing is that it's looking for a m a 205 00:16:18,480 --> 00:16:29,480 Speaker 1: immune response to a previous COVID infection. So it's actually um, 206 00:16:29,480 --> 00:16:34,920 Speaker 1: so how are we using it? So in practice, the 207 00:16:35,800 --> 00:16:40,480 Speaker 1: nasal swab the PC are well, let let me actually 208 00:16:40,520 --> 00:16:44,520 Speaker 1: explain that. So the most people know it by the 209 00:16:44,600 --> 00:16:48,200 Speaker 1: nose tests of nasal slops that people are getting quote 210 00:16:48,280 --> 00:16:52,560 Speaker 1: unquote slop for COVID. So that is a small Q 211 00:16:52,800 --> 00:16:56,640 Speaker 1: tip that they stick in your nose, in both sides 212 00:16:56,680 --> 00:17:01,720 Speaker 1: of your nose, your neres, and that actually is looking 213 00:17:01,760 --> 00:17:09,480 Speaker 1: for pieces of the genetic material of the virus. It's 214 00:17:09,520 --> 00:17:16,040 Speaker 1: a we call it a PIECR test, yes, polimerase chain 215 00:17:16,119 --> 00:17:20,720 Speaker 1: reaction text. So it's actually looking for the pieces. So 216 00:17:21,280 --> 00:17:26,280 Speaker 1: that test requires that you have a high enough amount 217 00:17:26,280 --> 00:17:29,280 Speaker 1: of virus and the nose in order for it to 218 00:17:29,359 --> 00:17:35,720 Speaker 1: be detected. Also, it's it requires that the person doing 219 00:17:35,760 --> 00:17:42,800 Speaker 1: the slab does it properly. Okay, in some cases we 220 00:17:42,920 --> 00:17:49,280 Speaker 1: suspect that someone has had COVID or has the coronavirus, 221 00:17:49,320 --> 00:17:54,240 Speaker 1: but that test continues to be negative. So what we 222 00:17:54,359 --> 00:17:59,480 Speaker 1: can do is see if the patient has mounted and 223 00:17:59,600 --> 00:18:04,640 Speaker 1: I mute response against the coronavirus, and that is when 224 00:18:04,720 --> 00:18:10,720 Speaker 1: we will do an antibody test. Okay, the other way 225 00:18:10,760 --> 00:18:13,960 Speaker 1: we use it. In some places, healthcare workers are being 226 00:18:14,040 --> 00:18:17,479 Speaker 1: screened because if you're a health care worker, you probably 227 00:18:17,480 --> 00:18:20,520 Speaker 1: it depends on the setting, but a lot of health 228 00:18:20,560 --> 00:18:26,720 Speaker 1: care workers have been exposed to coronavirus. So we're doing 229 00:18:27,119 --> 00:18:30,200 Speaker 1: the antibody is a blood test, so we're looking at 230 00:18:30,280 --> 00:18:34,560 Speaker 1: to see, okay, it has any of the health care workers. 231 00:18:34,640 --> 00:18:40,320 Speaker 1: Then exposure bit well have actually been expected. Because remember 232 00:18:40,400 --> 00:18:49,359 Speaker 1: you can have infection and not have symptoms, right, so 233 00:18:49,480 --> 00:18:53,320 Speaker 1: do you do you recommend that everyone should take this test? 234 00:18:56,080 --> 00:19:02,040 Speaker 1: Not necessarily Honestly, if you have not being sick at all, 235 00:19:02,600 --> 00:19:07,520 Speaker 1: healthy or no cost, no problems breathing them like nasal congestion, diarrhea, 236 00:19:08,320 --> 00:19:12,600 Speaker 1: no rash, that I would say no. They're in a 237 00:19:12,640 --> 00:19:16,919 Speaker 1: lot of places. Unfortunately, testing is still limited. If you 238 00:19:17,080 --> 00:19:23,240 Speaker 1: had no symptoms, I would just I would not do it. Now, 239 00:19:23,280 --> 00:19:28,960 Speaker 1: there have been some people who were sick in March, 240 00:19:29,800 --> 00:19:34,840 Speaker 1: but March was when the testing testing was extremely limited, 241 00:19:35,640 --> 00:19:38,560 Speaker 1: and so they think they may have had the infection 242 00:19:38,640 --> 00:19:43,160 Speaker 1: in March but was told to just self quarantine at home. 243 00:19:44,760 --> 00:19:47,480 Speaker 1: That person may want to talk to their doctors see 244 00:19:47,520 --> 00:19:50,720 Speaker 1: if they can get it in a body tests. Now 245 00:19:50,760 --> 00:19:54,000 Speaker 1: that it's more available, but it's not. It's tricky because 246 00:19:54,040 --> 00:20:00,600 Speaker 1: it's not available everywhere, and I if you're going well, 247 00:20:00,720 --> 00:20:02,920 Speaker 1: to be honest, I wouldn't go out of my way 248 00:20:03,000 --> 00:20:09,520 Speaker 1: to try to figure it out, right, I think unfortunately 249 00:20:09,640 --> 00:20:15,360 Speaker 1: we're still in the limited resources. So if you're feeling well, 250 00:20:16,320 --> 00:20:19,720 Speaker 1: just that is really good, and just be content and 251 00:20:19,760 --> 00:20:24,000 Speaker 1: the fact that you are feeling well, and leave those 252 00:20:24,119 --> 00:20:29,879 Speaker 1: resources to people who may need them because they're sick 253 00:20:30,040 --> 00:20:34,199 Speaker 1: right now. Right? Do you think the way that the 254 00:20:34,280 --> 00:20:41,120 Speaker 1: virus is being called about the media is accurate overall? 255 00:20:41,359 --> 00:20:47,600 Speaker 1: So I don't watch Fox News, so I don't know. 256 00:20:48,960 --> 00:20:54,520 Speaker 1: I cannot speak from Fox. However, I do watch m NBC, 257 00:20:54,960 --> 00:20:58,280 Speaker 1: I watched your local news every once in a while, 258 00:20:58,320 --> 00:21:05,280 Speaker 1: I watch CNN over I think it's pretty accurate. Yeah, 259 00:21:05,840 --> 00:21:09,520 Speaker 1: how especially, I think you get the most up to date, 260 00:21:10,080 --> 00:21:16,280 Speaker 1: the most accurate information from your local news because they 261 00:21:16,280 --> 00:21:21,679 Speaker 1: are just gonna that's their interests, and a lot of 262 00:21:21,720 --> 00:21:25,680 Speaker 1: the national news are focused in on the politics around 263 00:21:26,200 --> 00:21:34,600 Speaker 1: the virus and on the most heavily impacted states right now. Overa, 264 00:21:34,720 --> 00:21:38,280 Speaker 1: I think it's accurate and it's just informing people, especially 265 00:21:38,400 --> 00:21:41,680 Speaker 1: people who may not be living in areas where the 266 00:21:41,800 --> 00:21:46,840 Speaker 1: virus is heavily prevalent, that this is the problem and 267 00:21:47,040 --> 00:21:53,560 Speaker 1: other people, you know, people in other places aren't doing well. Yeah. 268 00:21:53,640 --> 00:21:56,040 Speaker 1: I don't know what slid in Atlanta was thinking, but 269 00:21:56,200 --> 00:21:57,960 Speaker 1: I think you're right. I think it was more son 270 00:21:58,040 --> 00:22:09,600 Speaker 1: a political standpoint. Yeah, Like it really is like very 271 00:22:09,720 --> 00:22:16,359 Speaker 1: frustrating because our country is so big, so it's we 272 00:22:16,440 --> 00:22:18,960 Speaker 1: look at our country is so big, so we look 273 00:22:19,000 --> 00:22:22,479 Speaker 1: at Italy saying they were a couple of weeks ahead 274 00:22:22,520 --> 00:22:25,800 Speaker 1: of us in regards to the impact of the virus 275 00:22:25,920 --> 00:22:29,840 Speaker 1: and now they're in a much better place. Cases are 276 00:22:29,880 --> 00:22:35,280 Speaker 1: relatively low. I would argue in the United States is 277 00:22:35,320 --> 00:22:39,199 Speaker 1: big we have and it was just really difficult to 278 00:22:39,200 --> 00:22:44,679 Speaker 1: get people to convince people to really buckle down. But 279 00:22:46,240 --> 00:22:50,920 Speaker 1: I blame the federal government. M I think that they 280 00:22:51,080 --> 00:22:59,199 Speaker 1: left a lot of okay. So I think in regards to, 281 00:22:59,480 --> 00:23:05,760 Speaker 1: you know, the administration, Trump administration knew about this pandemic 282 00:23:06,760 --> 00:23:11,280 Speaker 1: weeks before it actually hits. Whether they were gearing up 283 00:23:11,359 --> 00:23:15,440 Speaker 1: or how seriously they were taking it, I cannot comment 284 00:23:15,480 --> 00:23:19,560 Speaker 1: on that. However, when it hits, coming up with the 285 00:23:19,840 --> 00:23:22,960 Speaker 1: concrete plan as far as how they were going to test, 286 00:23:23,080 --> 00:23:27,480 Speaker 1: how they were going to test people for the virus, 287 00:23:27,480 --> 00:23:33,080 Speaker 1: how are we going to disseminate supplies. Unfortunately, they left 288 00:23:33,200 --> 00:23:38,720 Speaker 1: a lot of these the planning and the implementation to 289 00:23:38,760 --> 00:23:44,359 Speaker 1: the local and state government. Therefore, when they when the country, 290 00:23:44,520 --> 00:23:50,399 Speaker 1: when the when we were asked to shut down like 291 00:23:50,600 --> 00:23:55,840 Speaker 1: and wear masks and shut down, the local and state 292 00:23:55,840 --> 00:23:58,520 Speaker 1: governments were like, we're gonna just continue to do our 293 00:23:58,600 --> 00:24:02,840 Speaker 1: own things be because that's pretty much what we had 294 00:24:02,880 --> 00:24:06,400 Speaker 1: to do in the beginning. I think that things would 295 00:24:06,440 --> 00:24:09,920 Speaker 1: have been a lot different, Like things would have been 296 00:24:09,960 --> 00:24:15,200 Speaker 1: different if the borough government was like, look, this pandemic 297 00:24:15,320 --> 00:24:17,960 Speaker 1: is coming, this is how we're going to test people, 298 00:24:18,080 --> 00:24:21,800 Speaker 1: this is how we're gonna disseminate healthcare supplies, this is 299 00:24:21,840 --> 00:24:25,240 Speaker 1: the plans, like, this is what we need to do, X, y, 300 00:24:25,320 --> 00:24:29,000 Speaker 1: and z. Now, has the federal government's done a better 301 00:24:29,160 --> 00:24:33,679 Speaker 1: job and taking a leadership role in this pandemic, I 302 00:24:33,720 --> 00:24:37,600 Speaker 1: think that we would have had a lot more success 303 00:24:37,640 --> 00:24:43,399 Speaker 1: and people actually shutting down the economy in the local 304 00:24:43,520 --> 00:24:47,600 Speaker 1: and state government and wearing masks so forth and form 305 00:24:47,800 --> 00:24:53,320 Speaker 1: because they're seeing that from the top down. However, now 306 00:24:53,440 --> 00:24:58,199 Speaker 1: you know we got fifty fifty states, all these different 307 00:24:58,240 --> 00:25:03,320 Speaker 1: local territories, so you've got all these people making different decisions, 308 00:25:03,720 --> 00:25:05,680 Speaker 1: then it's gonna be a mess, and it's gonna be 309 00:25:05,760 --> 00:25:11,879 Speaker 1: an uncoordinated effort. And that's exactly what happened. And now, yeah, 310 00:25:12,920 --> 00:25:14,600 Speaker 1: so how do you think the virus will act my 311 00:25:14,680 --> 00:25:19,480 Speaker 1: school season come around. Well, I don't think the virus 312 00:25:19,560 --> 00:25:23,080 Speaker 1: is going to change. We have to change, like we 313 00:25:23,240 --> 00:25:28,200 Speaker 1: have to have a clear we have to have a 314 00:25:28,280 --> 00:25:34,120 Speaker 1: clear guideline how we're going to reopen schools, and reopening 315 00:25:34,200 --> 00:25:38,160 Speaker 1: schools is not going to be the same in every place. 316 00:25:39,040 --> 00:25:42,240 Speaker 1: The real thing is the virus is not as prevalent 317 00:25:42,720 --> 00:25:48,720 Speaker 1: in some places as it is in others, for example Arizona. Look, 318 00:25:48,920 --> 00:25:53,280 Speaker 1: it's mid July Arizona. The cases are going up, so 319 00:25:53,400 --> 00:25:58,920 Speaker 1: it's going to be extremely difficult for the school systems 320 00:25:59,040 --> 00:26:02,960 Speaker 1: in Arizona to have in person, have it the kids 321 00:26:03,160 --> 00:26:07,679 Speaker 1: go back to school, like go back to school in 322 00:26:07,720 --> 00:26:11,560 Speaker 1: a traditional setting where it's like here in Rhode Island. 323 00:26:13,040 --> 00:26:15,359 Speaker 1: Plan is for the kids to go back the school. 324 00:26:16,720 --> 00:26:19,640 Speaker 1: It's I'm not sure if they've laid out the details 325 00:26:19,720 --> 00:26:23,679 Speaker 1: of how they're gonna actually implement that, but because the 326 00:26:23,720 --> 00:26:29,600 Speaker 1: cases are low, the state can actually do that. So 327 00:26:30,920 --> 00:26:36,680 Speaker 1: it's very very very complex. Unfortunately. I think it all 328 00:26:36,760 --> 00:26:42,439 Speaker 1: depends on the prevalence of the virus in each community. 329 00:26:42,880 --> 00:26:49,280 Speaker 1: It all depends on the ability to contract to trace 330 00:26:50,359 --> 00:26:56,280 Speaker 1: uh context of positive cases, It all depends on it's 331 00:26:56,320 --> 00:27:00,920 Speaker 1: it's just really I think probably yeah, and I believe 332 00:27:01,960 --> 00:27:04,560 Speaker 1: to be honest, I feel bad for the parents, and 333 00:27:06,320 --> 00:27:10,639 Speaker 1: it is not It is not easy to have one child, 334 00:27:11,600 --> 00:27:17,200 Speaker 1: let alone multiple children in your home. You're trying to yeah, 335 00:27:17,320 --> 00:27:22,800 Speaker 1: you're trying to like ful feel the one line of 336 00:27:22,920 --> 00:27:26,160 Speaker 1: timon what if you don't have internet access? What if 337 00:27:26,160 --> 00:27:30,000 Speaker 1: you only have one computer and everybody has to use it? 338 00:27:30,600 --> 00:27:35,320 Speaker 1: So distance learning is not equal for every healthhold unfortunately. 339 00:27:37,200 --> 00:27:42,200 Speaker 1: So these are the things that Oh, and then the language, 340 00:27:42,200 --> 00:27:46,439 Speaker 1: but we didn't even go there. The language or cultural barrier. Okay, well, 341 00:27:46,680 --> 00:27:51,240 Speaker 1: the teacher and the child speaks English, but the parents 342 00:27:51,680 --> 00:27:56,800 Speaker 1: speak a different language and the child, you know, sometimes 343 00:27:56,880 --> 00:28:02,679 Speaker 1: they're too young to translate, or it's just complex concepts 344 00:28:02,800 --> 00:28:07,719 Speaker 1: that the teacher has to relate to the parents. And 345 00:28:07,720 --> 00:28:11,720 Speaker 1: if the teacher has let's say, the teacher normally has 346 00:28:11,760 --> 00:28:16,639 Speaker 1: thirty kids in some places, thirty cleep kids in the classroom, 347 00:28:17,040 --> 00:28:20,639 Speaker 1: and half of them speak, you know, a language that 348 00:28:20,720 --> 00:28:24,880 Speaker 1: the teacher does not speak, then it's like you can't. 349 00:28:25,560 --> 00:28:30,840 Speaker 1: It's just very unrealistic to have you know, one teacher 350 00:28:31,600 --> 00:28:38,960 Speaker 1: called ten you know, fifteen parents with a translator. It's 351 00:28:39,000 --> 00:28:42,040 Speaker 1: just very, very, very difficult. I'm not saying it's impossible. 352 00:28:42,040 --> 00:28:45,160 Speaker 1: I'm just saying it's difficult. And so I think things 353 00:28:45,200 --> 00:28:48,280 Speaker 1: are missed. It's just I don't have a solution. Education 354 00:28:48,400 --> 00:28:52,840 Speaker 1: is not mine, but it makes sense though is not 355 00:28:52,960 --> 00:28:56,520 Speaker 1: my specialty. Even with single parent households, like what they 356 00:28:56,520 --> 00:29:00,400 Speaker 1: have to go back to work, well, a lot of 357 00:29:00,440 --> 00:29:05,000 Speaker 1: people could could not go back to work, or they 358 00:29:05,040 --> 00:29:10,560 Speaker 1: have childcare for example. Let's say they have a relative 359 00:29:10,720 --> 00:29:15,280 Speaker 1: of friend, but that childcare provider can't be the teacher too. 360 00:29:15,600 --> 00:29:18,320 Speaker 1: You can't make it man, And so then the kid 361 00:29:18,440 --> 00:29:23,240 Speaker 1: wasn't just kid wasn't doing the work. Do you think 362 00:29:24,360 --> 00:29:28,400 Speaker 1: things would start to get better. I hope so, I 363 00:29:28,480 --> 00:29:36,240 Speaker 1: think so. I think that. Um. I remember in the 364 00:29:36,320 --> 00:29:41,880 Speaker 1: beginning of this, it was too scenario one scenario we 365 00:29:42,040 --> 00:29:47,280 Speaker 1: shut the country down aggressively, and we have a peak, 366 00:29:48,640 --> 00:29:52,600 Speaker 1: and then we have that would be the peak, and 367 00:29:52,600 --> 00:29:56,480 Speaker 1: then all the cases to be low and it would 368 00:29:56,520 --> 00:29:58,560 Speaker 1: just be low for a long time. But you so 369 00:29:58,680 --> 00:30:01,840 Speaker 1: you still have cases, but it would be extremely low. 370 00:30:02,680 --> 00:30:08,360 Speaker 1: The other model was not shutting down properly, and then 371 00:30:08,480 --> 00:30:11,600 Speaker 1: you have this high number of cases for a long 372 00:30:11,680 --> 00:30:15,360 Speaker 1: period of time. Unfortunately, I think we're in this high 373 00:30:15,520 --> 00:30:19,840 Speaker 1: that second model where we're having a lot of cases. 374 00:30:20,880 --> 00:30:24,440 Speaker 1: And this March April May jus like this is month four. 375 00:30:26,360 --> 00:30:30,440 Speaker 1: So I do think in twee twenty one things will 376 00:30:30,960 --> 00:30:38,800 Speaker 1: get better. However, I don't know when. I'm pretty sure 377 00:30:38,840 --> 00:30:43,520 Speaker 1: they're not gonna have a vaccine by flue season. It 378 00:30:43,640 --> 00:30:48,160 Speaker 1: just takes time for vaccines to be developed. You can't 379 00:30:48,240 --> 00:30:52,760 Speaker 1: rush back to development and people just started and like 380 00:30:54,120 --> 00:31:00,440 Speaker 1: you know, in the winter, maybe early mm hm oh. 381 00:31:01,240 --> 00:31:03,840 Speaker 1: I think I'm an optimist. I think it will get better. 382 00:31:04,600 --> 00:31:08,960 Speaker 1: It's gotten better in Rhode Island and other states. Yeah. 383 00:31:09,000 --> 00:31:13,040 Speaker 1: New York has been good, no depths and occurrence. That's good. 384 00:31:14,280 --> 00:31:16,960 Speaker 1: New York is better. I think the same people will 385 00:31:17,000 --> 00:31:19,840 Speaker 1: have you know, New York was hot for like weeks. 386 00:31:20,960 --> 00:31:24,120 Speaker 1: I think the same thing will happen for Texas, for Arizona, 387 00:31:24,440 --> 00:31:27,880 Speaker 1: for Florida, because they're gonna really start setting things down. 388 00:31:29,000 --> 00:31:32,320 Speaker 1: I just hope that after these flare ups from these 389 00:31:32,360 --> 00:31:37,120 Speaker 1: current states that things really die down. But unfortunately, I 390 00:31:37,160 --> 00:31:40,120 Speaker 1: think we're gonna be dealing with this for months. I 391 00:31:40,160 --> 00:31:42,720 Speaker 1: would not be surprised if we're still dealing with this 392 00:31:43,200 --> 00:31:50,080 Speaker 1: in the beginning of however, I think it will eventually 393 00:31:50,160 --> 00:31:52,640 Speaker 1: pass and things will get back to normal, but it 394 00:31:52,720 --> 00:31:55,840 Speaker 1: may be a new normal. Maybe people are gonna be 395 00:31:55,920 --> 00:32:01,520 Speaker 1: wearing that everywhere. Oh man, what do you think about 396 00:32:01,520 --> 00:32:09,400 Speaker 1: the doctors that are using different methods for treatment options? Yeah? So, uh, 397 00:32:10,400 --> 00:32:16,880 Speaker 1: God can be tricky. So you know, they just they 398 00:32:17,400 --> 00:32:22,920 Speaker 1: a clinical trial from room guessivere was was published, so 399 00:32:23,160 --> 00:32:28,200 Speaker 1: very various cases from gas of your headstone benefit decrease 400 00:32:28,680 --> 00:32:37,000 Speaker 1: state hospitalization days. Some of the other treatments like hydroxychloricuin 401 00:32:37,200 --> 00:32:41,840 Speaker 1: and Ziffer mice and uh, there are active clinical trials 402 00:32:41,960 --> 00:32:47,080 Speaker 1: actually looking at that for how use because for people 403 00:32:47,240 --> 00:32:53,760 Speaker 1: who were either more affluent or had more connections started 404 00:32:53,800 --> 00:33:00,080 Speaker 1: taking hydroxic corp when early in the pan damage. But 405 00:33:00,160 --> 00:33:03,240 Speaker 1: we don't know if it works. We don't. We absolutely 406 00:33:03,240 --> 00:33:06,440 Speaker 1: don't know. So there have been a lot of a 407 00:33:06,520 --> 00:33:13,120 Speaker 1: lot of different clinical trials. Callitra is another which is 408 00:33:13,160 --> 00:33:21,160 Speaker 1: a former hip well HIV medication to treat coronavirus. There's 409 00:33:21,240 --> 00:33:27,880 Speaker 1: just so much. We don't know. For severe cases, there 410 00:33:28,080 --> 00:33:32,600 Speaker 1: is evidence that room death severe which is IVY medication 411 00:33:34,360 --> 00:33:38,200 Speaker 1: that is only offered to people in the hospital, has 412 00:33:38,240 --> 00:33:45,040 Speaker 1: shown some benefit. However, we don't have anything. For people 413 00:33:45,800 --> 00:33:48,160 Speaker 1: who are in the community who aren't sick enough to 414 00:33:48,200 --> 00:33:51,880 Speaker 1: be in hospital, we say we just treated like the 415 00:33:52,080 --> 00:33:57,280 Speaker 1: blue stay at home, rest, drink plenty of fluids you 416 00:33:57,280 --> 00:34:02,400 Speaker 1: can take if your muscles, her body her and for 417 00:34:02,480 --> 00:34:07,480 Speaker 1: the fever. So it's still a lot of different challenges. 418 00:34:07,960 --> 00:34:11,280 Speaker 1: Steroids are being used, I'm not sure on an out 419 00:34:11,640 --> 00:34:16,120 Speaker 1: patient basis, but definitely on an impatient basis to decreases 420 00:34:16,320 --> 00:34:23,000 Speaker 1: swelling the lungs or information that people say have shown benefits. 421 00:34:23,040 --> 00:34:29,160 Speaker 1: So it's a lot. It's a lot of unknowns. And 422 00:34:29,600 --> 00:34:33,719 Speaker 1: when you say people are willing to take whatever, yeah, 423 00:34:33,760 --> 00:34:38,920 Speaker 1: I'm not doing that. I ain't taking whatever. Ye. My 424 00:34:39,040 --> 00:34:41,160 Speaker 1: last question is a lot of my listeners is writing 425 00:34:41,160 --> 00:34:44,279 Speaker 1: this in because people love their animals. Um. Do you 426 00:34:44,320 --> 00:34:46,200 Speaker 1: think there's a chance that parts would be able to 427 00:34:46,200 --> 00:34:56,839 Speaker 1: get COVID nineteen? Um? I think that's there. If I'm 428 00:34:56,840 --> 00:35:01,000 Speaker 1: not mistaken. I think that they have shown that. I 429 00:35:01,040 --> 00:35:05,120 Speaker 1: can't remember what type of animals have gotten COVID nineteen. 430 00:35:06,320 --> 00:35:16,000 Speaker 1: But it's a possibility. Yes, infection is that humans get 431 00:35:17,239 --> 00:35:25,359 Speaker 1: that animals can get too, But I'm not sure. I'm 432 00:35:25,360 --> 00:35:28,319 Speaker 1: not quite sure. I would have to look into the 433 00:35:28,400 --> 00:35:33,319 Speaker 1: literature and see what's been written up about this. I 434 00:35:33,440 --> 00:35:38,839 Speaker 1: understand that you love your pet, but I really do 435 00:35:38,960 --> 00:35:44,879 Speaker 1: hope they don't get COVID nineteen. I would, Yeah, if 436 00:35:44,920 --> 00:35:48,120 Speaker 1: you're continguous to humans, I would assume that you could 437 00:35:48,120 --> 00:35:51,520 Speaker 1: potentially be contagious for your pet too. Nine Know a 438 00:35:51,600 --> 00:35:54,520 Speaker 1: dog is a man's best friend, but maybe you could 439 00:35:54,600 --> 00:35:59,000 Speaker 1: distance yourself from your dog too, just to prevent the 440 00:35:59,160 --> 00:36:04,520 Speaker 1: dog from getting Say mm hmm, well, I really appreciate 441 00:36:04,560 --> 00:36:06,080 Speaker 1: you taking the time to speak to us. I feel 442 00:36:06,120 --> 00:36:08,080 Speaker 1: like the last time we talked, I could definitely hear 443 00:36:08,719 --> 00:36:11,239 Speaker 1: you sound a little tired. This time, I'm pretty sure 444 00:36:11,280 --> 00:36:17,960 Speaker 1: you're like really busy. Yeah, yeah I was. I was 445 00:36:18,160 --> 00:36:22,399 Speaker 1: definitely gone. Are you taking any days off anytime soon? 446 00:36:24,600 --> 00:36:28,480 Speaker 1: I had a couple of days off two weeks ago. 447 00:36:28,880 --> 00:36:32,439 Speaker 1: I was told that was not enough time. I am 448 00:36:32,560 --> 00:36:36,040 Speaker 1: gonna take vacation in August. You should. My days are 449 00:36:36,120 --> 00:36:40,799 Speaker 1: not so busy now, so I'm very happy about that. 450 00:36:40,880 --> 00:36:44,239 Speaker 1: But yeah, I'm definitely gonna say, maybe a week or 451 00:36:44,280 --> 00:36:47,920 Speaker 1: so off in a couple of weeks. Yeah, it take 452 00:36:48,000 --> 00:36:50,200 Speaker 1: some time off for yourself as well. A lot going on. 453 00:36:50,320 --> 00:36:57,160 Speaker 1: I feel like you see it every day, so yeah. Yeah. Well, 454 00:36:57,200 --> 00:37:00,200 Speaker 1: if I have any questions, concerns, or comments about this 455 00:37:00,880 --> 00:37:03,960 Speaker 1: special episode from our doctor, please make sure to email 456 00:37:04,000 --> 00:37:07,839 Speaker 1: me at Hello at the PhD Pod. Until my guest, 457 00:37:07,920 --> 00:37:10,080 Speaker 1: as always, thank you so much for taking the time 458 00:37:10,120 --> 00:37:15,080 Speaker 1: about to speak with us, and until next time, everyone Later,